Herself’s Artificial Intelligence

Humans, meet your replacements.

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Multi agent systems become more regretfully human

‘Science’ published a paper by M.D.Cohen ‘Learning with Regret’ This paper is about an economic prediction system that lets the agents learn from past errors. Agents look back at previous decisions to see what better outcomes may have happened if they had chose differently. In doing so agents make better future decisions.

Not everyone feels regret is useful for economic agents. Yu-Han Chang argues that systems that minimize regret can perform better than ones using regret.

More information:
Micheal D Cohen
Center for Complex Systems

Papers:
Rational Competative analysis (pdf )
Recognizing the New: A Multi-Agent Model of Analogy in Strategic Decision Making ( pdf )
Rewarding Regret (pdf)
Diversity and Communication in Teams: Improving Problem Solving or Creating Confustion? (pdf)
Economics papers by Massimo Warglien

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